Abstract

We present Young Supernova Experiment grizy photometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates and investigating their contributions toward the SN Ia intrinsic scatter (post-standardization residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter, σ Rel: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution toward the total intrinsic scatter, σ 0, from within-galaxy variations about the siblings’ common properties. It also affects the combined distance uncertainty. We present analytic formulae for computing a σ Rel posterior from individual siblings distances (estimated using any SN model). Applying a newly trained BayeSN model, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wide σ Rel posterior means σ Rel ≈ σ 0 is not ruled out. We thus combine the distances by marginalizing over σ Rel with an informative prior: σ Rel ∼ U(0, σ 0). Simultaneously fitting the trio’s light curves improves constraints on distance and each sibling’s individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore, σ Rel marginalization yields robust estimates of siblings distances for cosmology, as well as dust parameters for sibling–host correlation studies. Incorporating NGC 3147's Cepheid distance yields H 0 = 78.4 ± 6.5 km s−1 Mpc−1. Our work motivates analyses of homogeneous siblings samples, to constrain σ Rel and its SN-model dependence.

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